Application Sensitive Energy Management Framework for Storage Systems

Rapidly escalating energy and cooling costs, especially those related to the energy consumption of storage systems, have become a concern for data centers, primarily because the amount of digital data that needs storage is increasing daily. In response, a multitude of energy saving approaches that take into account storage-device-level input/output (I/O) behaviors have been proposed. The trouble is that numerous critical applications such as database systems or web commerce applications are in constant operation at data centers, and the conventional approaches that only utilize storage-device-level I/O behaviors do not produce sufficient energy savings. It may be possible to dramatically reduce storage-related energy consumption without degrading application performance levels by utilizing application-level I/O behaviors. However, such behaviors differ from one application to another, and it would be too expensive to tailor methods to individual applications. As a way of solving this problem, we propose a universal storage energy management framework for runtime storage energy savings that can be applied to any type of application. The results of evaluations show that the use of this framework results in substantive energy savings compared with the traditional approaches that are used while applications are running.